o ॵi @s0ddlmZddlmZddlZddlmZmZddl m Z zddl m Z m Z mZmZWn6eybeeeZe deeddeedd eedd gd d Z ddl m Z m Z mZmZYnwGd ddejjZGdddejjZdejdejdejdejfddZdejdejdejfddZdS)N)Tuple) custom_bwd custom_fwd)load)ailut_cbackwardailut_cforward lut_cbackward lut_cforward cudaops_ailutAilutzcsrc/ailut_transform.cppzcsrc/ailut_transform_cpu.cppzcsrc/ailut_transform_cuda.cuT)namesourcesverbosec@sZeZdZeeejddejdejdejfddZee dejde ejfdd Z d S) LUTTransformFunction cast_inputsimglutreturncCs~|}|}|dksJd|dvsJd||d|d|d|df}t|||||||S) NConly support 2D image with batch and channel dimensions (4D tensor)=only support 3D lookup table with batch dimension (5D tensor)r) contiguous ndimension new_zerossizer save_for_backward)ctxrroutputr$U/home/ubuntu/.local/lib/python3.10/site-packages/modelscope/ops/ailut/pyinterfaces.pyforwards"  zLUTTransformFunction.forward grad_outputcCs>|}|j\}}t|}t|}t|||||||fSN)r saved_tensorstorch zeros_liker)r"r'rrgrad_imggrad_lutr$r$r%backward/s    zLUTTransformFunction.backwardN) __name__ __module__ __qualname__ staticmethodrr*float32Tensorr&rrr.r$r$r$r%rs  "rc @s`eZdZeeejddejdejdejdejfddZ ee dejde ejfd d Z d S) AiLUTTransformFunctionrrrverticesrcCs|}|}|}|dksJd|dvs Jd|dks*Jd||d|d|d |df}t|||||||||S) NrrrrrzKonly support 1D vertices list with batch and channel dimensions (3D tensor)rrr)rrrr rr!)r"rrr6r#r$r$r%r&@s$"zAiLUTTransformFunction.forwardr'cCsP|}|j\}}}t|}t|}t|}t||||||||||fSr()rr)r*r+r)r"r'rrr6r,r-grad_verr$r$r%r.Xs     zAiLUTTransformFunction.backwardN) r/r0r1r2rr*r3r4tensorr&rrr.r$r$r$r%r5>s "r5rrr6rcCst|||S)aAdaptive Interval 3D Lookup Table Transform (AiLUT-Transform). Args: img (torch.Tensor): input image of shape (b, 3, h, w). lut (torch.Tensor): output values of the 3D LUT, shape (b, 3, d, d, d). vertices (torch.Tensor): sampling coordinates along each dimension of the 3D LUT, shape (b, 3, d). Returns: torch.Tensor: transformed image of shape (b, 3, h, w). )r5apply)rrr6r$r$r%ailut_transformjs r:cCs t||S)aStandard 3D Lookup Table Transform. Args: img (torch.Tensor): input image of shape (b, 3, h, w). lut (torch.Tensor): output values of the 3D LUT, shape (b, 3, d, d, d). Returns: torch.Tensor: transformed image of shape (b, 3, h, w). )rr9)rrr$r$r% lut_transformys r;)os.pathpathosptypingrr*torch.cuda.amprrtorch.utils.cpp_extensionrr rrrr ImportErrorabspathdirname__file__CUR_DIRjoinautogradFunctionrr5r4r:r;r$r$r$r%s6      %,